Val Piora Wheatear: Untitled

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library(GeoPressureR)
library(leaflet)
library(leaflet.extras)
library(raster)
library(dplyr)
library(ggplot2)
library(kableExtra)
library(plotly)
library(GeoLocTools)
setupGeolocation()
knitr::opts_chunk$set(echo = FALSE)
load(paste0("../data/1_pressure/", params$gdl_id, "_pressure_prob.Rdata"))
load(paste0("../data/2_light/", params$gdl_id, "_light_prob.Rdata"))
load(paste0("../data/3_static/", params$gdl_id, "_static_prob.Rdata"))
load(paste0("../data/4_basic_graph/", params$gdl_id, "_basic_graph.Rdata"))
load(paste0("../data/5_wind_graph/", params$gdl_id, "_wind_graph.Rdata"))
col <- rep(RColorBrewer::brewer.pal(8, "Dark2"), times = ceiling(max(pam$sta$sta_id) / 8))

Settings used

All the results produced here are generated with (1) the raw geolocator data, (2) the labeled files of pressure and light and (3) the parameters listed below.

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kable(gpr) %>% scroll_box(width = "100%")

gdl_id	keep	crop_start	crop_end	thr_dur	extent_N	extent_W	extent_S	extent_E	map_scale	map_max_sample	map_margin	prob_map_s	prob_map_s_calib	prob_map_thr	shift_k	kernel_adjust	calib_lon	calib_lat	calib_1_start	calib_1_end	calib_2_start	calib_2_end	calib_2_lon	calib_2_lat	prob_light_w	thr_prob_percentile	thr_gs	thr_as	RingNo	scientific_name	common_name	mass	wing_span	Color	sta_id_winter
26IL	9	2020-07-14	2021-06-30	0	51	-18	5	16	4	300	30	1	1.3	0.9	0	1.4	8.70603	46.5492	2020-07-14	2020-09-11	2021-05-08	2021-06-30	NA	NA	0.09	0.95	120	100	N566945	Oenanthe oenanthe	Northern wheatear	NA	NA	#EF553B	14

Pressure timeserie

The labeling of pressure data is illustrated with this figure. The black dots indicates the pressure datapoint not considered in the matching. Each stationary period is illustrated by a different colored line.

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pressure_na <- pam$pressure %>%
  mutate(obs = ifelse(isoutlier | sta_id == 0, NA, obs))
p <- ggplot() +
  geom_line(data = pam$pressure, aes(x = date, y = obs), colour = "grey") +
  # geom_point(data = subset(pam$pressure, isoutlier), aes(x = date, y = obs), colour = "black") +
  # geom_line(data = pressure_na, aes(x = date, y = obs, color = factor(sta_id)), size = 0.5) +
  geom_line(data = do.call("rbind", shortest_path_timeserie) %>% filter(sta_id > 0), aes(x = date, y = pressure0, col = factor(sta_id))) +
  theme_bw() +
  scale_colour_manual(values = col) +
  scale_y_continuous(name = "Pressure(hPa)")

ggplotly(p, dynamicTicks = T) %>% layout(showlegend = F)

Pressure calibration

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pressure_ts_bind <- do.call("rbind", shortest_path_timeserie) %>%
  filter(!is.na(sta_id))

pam$pressure %>%
  left_join(pressure_ts_bind %>% dplyr::select(c("date", "pressure0")), by = "date") %>%
  mutate(diff = ifelse(is.na(pressure0), 0, obs - pressure0)) %>%
  filter(sta_id > 0 & !isoutlier) %>%
  group_by(sta_id) %>%
  mutate(sta_id = paste0(sta_id, " (SD=", round(sd(diff), 2), " ; N=", n(), ")")) %>%
  ggplot(aes(x = diff)) +
  geom_histogram(aes(y = (..count..) / tapply(..count.., ..PANEL.., sum)[..PANEL..]), binwidth = .2) +
  facet_wrap(~sta_id) +
  scale_x_continuous(name = "Pressure Geolocator - best match ERA5 (hPa)") +
  scale_y_continuous(name = "Normalized histogram")

Light

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raw_geolight <- pam$light %>%
  transmute(
    Date = date,
    Light = obs
  )
lightImage(tagdata = raw_geolight, offset = 0)
tsimagePoints(twl$twilight,
  offset = 0, pch = 16, cex = 1.2,
  col = ifelse(twl$deleted, "grey20", ifelse(twl$rise, "firebrick", "cornflowerblue"))
)
abline(v = gpr$calib_2_start, lty = 1, col = "firebrick", lwd = 1.5)
abline(v = gpr$calib_1_start, lty = 1, col = "firebrick", lwd = 1.5)
abline(v = gpr$calib_2_end, lty = 2, col = "firebrick", lwd = 1.5)
abline(v = gpr$calib_1_end, lty = 2, col = "firebrick", lwd = 1.5)

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hist(z, freq = F)
lines(fit_z, col = "red")

The probability map resulting from light data alone can be seen below.

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li_s <- list()
l <- leaflet(width = "100%") %>%
  addProviderTiles(providers$Stamen.TerrainBackground) %>%
  addFullscreenControl()
for (i_r in seq_len(length(light_prob))) {
  i_s <- metadata(light_prob[[i_r]])$sta_id
  info <- pam$sta[pam$sta$sta_id == i_s, ]
  info_str <- paste0(i_s, " | ", info$start, "->", info$end)
  li_s <- append(li_s, info_str)
  l <- l %>% addRasterImage(light_prob[[i_r]], opacity = 0.8, colors = "OrRd", group = info_str)
}
l %>%
  addCircles(lng = gpr$calib_lon, lat = gpr$calib_lat, color = "black", opacity = 1) %>%
  addLayersControl(
    overlayGroups = li_s,
    options = layersControlOptions(collapsed = FALSE)
  ) %>%
  hideGroup(tail(li_s, length(li_s) - 1))

Light vs Pressure

We can compare light and pressure location at long stationary stopover (>5 days). By assuming the best match of the pressure to be the truth, we can plot the histogram of the zenith angle and compare to the fit of kernel density at the calibration site.

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 raw_geolight <- pam$light %>%
    transmute(
      Date = date,
      Light = obs
    )
 dur <- unlist(lapply(pressure_prob, function(x) difftime(metadata(x)$temporal_extent[2],metadata(x)$temporal_extent[1], units = "days" )))
  long_id <- which(dur>5)

  par(mfrow = c(2, 3))
  for (i_s in long_id){
    twl_fl <- twl %>%
      filter(!deleted) %>%
      filter(twilight>shortest_path_timeserie[[i_s]]$date[1] & twilight<tail(shortest_path_timeserie[[i_s]]$date,1))
    sun <-  solar(twl_fl$twilight)
    z_i <- refracted(zenith(sun, shortest_path_timeserie[[i_s]]$lon[1], shortest_path_timeserie[[i_s]]$lat[1]))
    hist(z_i, freq = F, main = paste0("sta_id=",i_s, " | ",nrow(twl_fl),"twls"))
    lines(fit_z, col = "red")
    xlab("Zenith angle")
  }

Similarly, we can plot the line of sunrise/sunset at the best match of pressure (yellow line) and compare to the raw and labeled light data.

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  lightImage(
    tagdata = raw_geolight,
    offset = gpr$shift_k / 60 / 60
  )
  tsimagePoints(twl$twilight,
                offset = gpr$shift_k / 60 / 60, pch = 16, cex = 1.2,
                col = ifelse(twl$deleted, "grey20", ifelse(twl$rise, "firebrick", "cornflowerblue"))
  )
  for (ts in shortest_path_timeserie){
    twl_fl <- twl %>%
      filter(twilight>ts$date[1] & twilight<tail(ts$date,1))
    if (nrow(twl_fl)>0){
    tsimageDeploymentLines(twl_fl$twilight,
                           lon = ts$lon[1], ts$lat[1],
                           offset = gpr$shift_k / 60 / 60, lwd = 3,col = adjustcolor("orange", alpha.f = 0.5))
      
    }
  }

Stationay period information

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read_csv(paste0("../reports/figure_print/table_transition/transition_", params$gdl_id, ".csv")) %>% kable() %>% scroll_box(width = "100%")

…1	sta_id_s	sta_id_t	flight_duration	as_m	as_s	gs_m	gs_s	ws_m	ws_s	dist_m	dist_s	ws_m_support	ws_m_drift	start_flight	end_flight	sunrise	sunset	as_sp	gs_sp	ws_sp	dist_sp	ws_sp_support	ws_sp_drift	alt_min	alt_max	alt_mean	alt_med	alt_sumdabsdiff	alt_sumposdiff	gdl_id
1	1	2	4.5	45.12684	7.699357	47.59807	8.924990	7.306054	1.8742216	214.19132	40.16245	2.9678015	6.676120	2020-09-10 18:30:00	2020-09-10 23:00:00	2020-09-11 04:35:55	2020-09-10 18:17:04	42.95123	45.191001	6.198175	203.35951	2.6093231	5.6221714	2611.02252	4387.7198	3423.8121	3346.2346	3.797248e+03	2255.7744888	26IL
2	2	3	2.0	35.13200	16.944640	35.49125	16.706746	4.661648	1.9628818	70.98250	33.41349	0.6635775	4.614177	2020-09-11 18:00:00	2020-09-11 20:00:00	2020-09-12 04:37:45	2020-09-11 18:19:08	28.07729	27.782334	3.752254	55.56467	-0.0431338	3.7520056	2401.30535	3460.9959	3018.0717	3144.4415	1.593267e+03	533.5763162	26IL
3	3	4	6.0	94.20691	4.926342	99.68582	4.758000	15.774468	1.6132538	598.11494	28.54800	6.5764395	14.338211	2020-09-12 18:00:00	2020-09-13 00:00:00	2020-09-13 04:39:23	2020-09-12 18:16:37	97.05710	103.269581	14.871402	619.61748	7.0963959	13.0690385	222.78219	3763.2314	1941.3909	1584.4365	5.262030e+03	1413.8544764	26IL
4	4	5	3.5	85.18337	9.875898	100.53283	9.597204	17.644566	1.0702466	351.86489	33.59022	15.7260744	8.001331	2020-09-13 19:00:00	2020-09-13 22:30:00	2020-09-14 04:49:28	2020-09-13 18:04:28	81.46064	97.702727	17.985151	341.95954	16.5474037	7.0462098	62.39886	1681.2252	1065.9077	1066.2195	3.112430e+03	2032.0246912	26IL
5	5	6	12.0	37.34174	10.731390	65.01571	9.047854	41.184975	2.3353028	780.18858	108.57425	34.8288058	21.980819	2020-09-25 17:30:00	2020-09-26 05:30:00	2020-09-26 05:05:32	2020-09-25 17:51:06	39.65199	72.284204	41.908423	867.41045	37.4151017	18.8792509	230.53934	2421.5464	845.7293	756.0839	7.064001e+03	3210.8762344	26IL
6	6	7	12.0	51.22079	19.893162	61.85445	19.740763	13.866949	2.9803719	742.25343	236.88915	11.2740185	8.073957	2020-09-26 17:30:00	2020-09-27 05:30:00	2020-09-27 05:13:24	2020-09-26 17:53:23	35.67458	46.209731	14.419071	554.51677	11.5838525	8.5862667	311.16417	2894.3226	1223.6625	770.2077	6.966603e+03	3581.1964183	26IL
7	7	8	11.5	53.42417	19.447018	45.33577	18.707780	14.038087	4.1383844	521.36138	215.13948	-6.6365027	12.370316	2020-09-27 18:00:00	2020-09-28 05:30:00	2020-09-28 05:13:45	2020-09-27 17:58:56	46.47545	40.920954	14.221542	470.59097	-3.4602207	13.7941704	408.44626	4530.1083	2311.9055	1993.0802	1.048085e+04	5217.2122547	26IL
8	8	9	6.0	31.80557	15.777779	42.96682	18.765532	21.013885	3.3562772	257.80091	112.59319	14.8502583	14.867858	2020-09-28 19:30:00	2020-09-29 01:30:00	2020-09-29 05:20:54	2020-09-28 17:57:58	25.70336	38.403896	17.420912	230.42337	14.5517127	9.5778825	403.09012	3832.0067	1603.1387	1420.3153	7.227556e+03	3629.4639193	26IL
9	9	10	4.5	34.15655	14.789111	52.35748	18.674858	25.927844	4.6756423	235.60864	84.03686	21.4571859	14.554803	2020-09-29 20:30:00	2020-09-30 01:00:00	2020-09-30 05:29:01	2020-09-29 18:04:10	26.57687	50.553917	27.403024	227.49263	25.7180281	9.4609078	295.82028	1010.2604	776.1838	910.8920	2.454095e+03	1171.4754585	26IL
10	10	11	3.0	31.62360	16.625351	30.00403	17.167722	19.104229	1.9164207	90.01208	51.50317	4.4187556	18.586182	2020-09-30 21:00:00	2020-10-01 00:00:00	2020-10-01 05:29:09	2020-09-30 18:11:24	26.09332	9.222896	21.109630	27.66869	-8.1418706	19.4763039	244.80495	2275.3752	1263.6565	1161.1450	4.032587e+03	2002.0171669	26IL
11	11	12	2.0	53.67868	18.006617	45.69394	21.854695	26.590964	1.6142130	91.38788	43.70939	-0.9452600	26.574158	2020-10-01 23:30:00	2020-10-02 01:30:00	2020-10-02 05:32:21	2020-10-01 18:10:38	42.81084	42.159192	25.315215	84.31838	6.9437930	24.3442779	243.39175	1581.3703	692.5199	404.8812	2.666883e+03	1337.9785136	26IL
12	12	13	1.5	38.08684	17.199775	39.13299	18.128744	4.073313	2.2656539	58.69948	27.19312	1.2441520	3.878655	2020-10-05 19:00:00	2020-10-05 20:30:00	2020-10-06 05:35:03	2020-10-05 18:10:26	30.50455	35.375515	6.933875	53.06327	5.2151638	4.5695399	242.62245	1614.1480	803.2752	678.1653	2.690868e+03	1371.5255265	26IL
13	13	14	1.0	33.49898	15.085294	42.22259	21.691864	27.621195	0.8933315	42.22259	21.69186	16.8570419	21.880827	2020-10-12 10:00:00	2020-10-12 11:00:00	2020-10-12 05:37:14	2020-10-11 18:07:57	23.37225	26.531642	28.463887	26.53164	18.2397052	21.8519114	248.20466	249.0924	248.5006	248.2047	8.877791e-01	0.8877791	26IL
14	14	15	8.5	32.23714	11.202116	31.30342	10.390311	16.625083	4.5700670	266.07907	88.31764	3.4670983	16.259539	2021-03-21 18:30:00	2021-03-22 03:00:00	2021-03-22 05:37:59	2021-03-21 18:39:22	27.24955	32.381274	19.482007	275.24083	10.5857078	16.3551641	237.84127	2429.8638	1660.5846	1845.8967	5.911561e+03	3038.5067879	26IL
15	15	16	10.0	28.14609	12.509322	44.38172	19.073759	45.345213	6.0074208	443.81717	190.73759	36.4307958	26.999731	2021-03-22 18:30:00	2021-03-23 04:30:00	2021-03-23 05:28:58	2021-03-22 18:30:51	26.35666	22.606111	48.427168	226.06111	47.8090463	7.7126946	384.20835	5147.8907	3446.1291	3306.6213	1.219558e+04	6203.8245658	26IL
16	16	17	6.5	30.50453	12.633950	32.06253	18.070610	25.310632	3.4697304	208.40646	117.45896	11.5104422	22.541912	2021-03-23 18:00:00	2021-03-24 00:30:00	2021-03-24 05:32:01	2021-03-23 18:23:17	26.33055	16.677430	24.968177	108.40330	6.2434364	24.1749743	566.86240	1024.1657	742.6747	711.0141	2.491505e+03	1210.0969654	26IL
17	17	18	7.5	38.32701	15.095112	60.05750	16.354917	33.268972	3.6666602	450.43125	122.66188	27.0138452	19.418462	2021-03-24 18:30:00	2021-03-25 02:00:00	2021-03-25 05:42:35	2021-03-24 18:27:38	26.66967	44.477531	34.960908	333.58148	27.9831716	20.9572714	299.45156	825.4899	620.9416	618.4195	1.698015e+03	700.3692787	26IL
18	18	19	2.5	31.55260	14.211586	35.34981	16.722978	14.971902	2.4362543	88.37453	41.80745	6.7638364	13.356960	2021-03-25 23:00:00	2021-03-26 01:30:00	2021-03-26 05:42:00	2021-03-25 18:38:26	26.14501	33.204120	14.594859	83.01030	9.5163171	11.0656951	266.80720	1557.3163	864.4505	758.7155	4.717633e+03	2378.2148754	26IL
19	19	20	19.0	34.47635	10.314468	46.57863	13.367300	23.843151	8.5833947	884.99401	253.97870	16.6325858	17.083704	2021-04-04 18:30:00	2021-04-05 13:30:00	2021-04-05 05:15:25	2021-04-04 18:40:20	32.31311	49.864257	32.879961	947.42088	25.3026791	20.9968151	233.71401	3800.0737	1815.5431	1306.6843	1.033126e+04	5218.5616728	26IL
20	20	21	11.0	30.52391	11.942926	36.30105	13.218733	14.293712	6.8679621	399.31158	145.40606	8.1315453	11.755347	2021-04-05 18:30:00	2021-04-06 05:30:00	2021-04-06 05:18:39	2021-04-05 18:33:13	30.18107	36.330827	7.283679	399.63910	6.3593933	3.5510706	243.51023	2690.9202	1796.0888	2009.9493	7.360204e+03	3636.9179884	26IL
21	21	22	11.0	45.07262	13.075139	72.74487	13.072703	33.591963	5.7160034	800.19356	143.79973	30.1649774	14.781546	2021-04-08 18:30:00	2021-04-09 05:30:00	2021-04-09 05:04:18	2021-04-08 18:44:41	29.94167	56.477208	33.467214	621.24929	30.2177280	14.3855240	248.02299	3450.7274	2280.8495	2339.0131	8.201982e+03	4570.9650450	26IL
22	22	23	1.5	34.77391	15.675047	49.25761	24.711618	34.782635	3.9474155	73.88641	37.06743	24.6349648	24.555044	2021-04-09 21:30:00	2021-04-09 23:00:00	2021-04-10 05:04:20	2021-04-09 18:46:19	30.20194	47.976299	29.244080	71.96445	23.3947239	17.5471690	1135.18311	2323.0432	1707.6330	1686.1528	2.292724e+03	1104.8643193	26IL
23	23	24	1.5	33.35247	16.038846	34.15071	17.093765	19.318669	2.1071288	51.22607	25.64065	6.2530862	18.278673	2021-04-11 23:30:00	2021-04-12 01:00:00	2021-04-12 05:00:16	2021-04-11 18:50:36	30.00011	23.945136	19.138617	35.91770	0.8279265	19.1207012	1016.68546	1769.6671	1386.2205	1379.2648	1.455037e+03	752.9816328	26IL
24	24	25	13.0	46.77860	15.985980	50.65283	15.346765	13.224389	2.2639938	658.48683	199.50794	5.4523734	12.048074	2021-04-23 19:00:00	2021-04-24 08:00:00	2021-04-24 04:37:19	2021-04-23 19:00:21	27.52238	32.012814	12.281785	416.16658	6.5314678	10.4010658	142.43321	2561.7290	1665.0934	1785.5989	8.560394e+03	3776.1119153	26IL
25	25	26	9.5	35.22614	16.518789	47.20874	18.599922	17.399100	5.1395163	448.48300	176.69925	13.6681526	10.766164	2021-04-24 19:00:00	2021-04-25 04:30:00	2021-04-25 04:21:37	2021-04-24 19:08:36	24.53766	41.070270	16.543103	390.16757	16.5368344	0.4553737	69.03776	3401.6966	1890.7808	1705.8434	1.077716e+04	5386.5717627	26IL
26	26	28	12.5	19.53331	9.656026	22.50134	11.748562	15.598667	7.5812435	281.26675	146.85702	8.1790324	13.282388	2021-04-25 19:00:00	2021-04-26 01:30:00	2021-04-26 04:01:00	2021-04-25 19:10:04	26.48852	28.893838	27.087730	361.17298	15.0024605	22.5537424	NA	NA	NA	NA	NA	NA	26IL
27	28	31	11.5	12.86087	5.199985	18.38594	7.545220	11.162948	2.2372422	211.43826	86.77003	8.0836775	7.698414	2021-05-03 17:00:00	2021-05-04 02:00:00	2021-05-04 03:32:05	2021-05-03 19:09:08	14.25841	24.706092	13.091103	284.12006	11.7069428	5.8587099	NA	NA	NA	NA	NA	NA	26IL
28	31	32	1.5	39.88277	14.228051	34.74703	14.596728	6.771646	2.1530288	52.12054	21.89509	-4.8554383	4.720160	2021-05-05 23:00:00	2021-05-06 00:30:00	2021-05-06 03:40:13	2021-05-05 19:14:47	28.53769	18.526034	10.021336	27.78905	-10.0064192	0.5465787	1330.77282	1991.9270	1728.3621	1795.3743	1.413017e+03	1037.0853895	26IL
29	32	33	0.5	37.73646	15.640609	39.19387	24.704418	14.221762	3.2692795	19.59694	12.35221	4.0105472	13.644560	2021-05-06 13:00:00	2021-05-06 13:30:00	2021-05-07 03:40:26	2021-05-06 19:16:55	41.48032	55.580542	14.144056	27.79027	14.1113578	0.9611980	1415.41112	2014.2232	1714.8171	1714.8171	5.988120e+02	0.0000000	26IL
30	33	34	1.0	29.90859	16.679628	27.30164	16.981306	5.408673	1.0162178	27.30164	16.98131	-2.1956594	4.942957	2021-05-07 18:30:00	2021-05-07 19:30:00	2021-05-08 03:50:45	2021-05-07 19:16:33	20.25416	19.146616	5.206797	19.14662	-0.4315993	5.1888780	1491.49389	2056.3858	1686.4042	1511.3331	5.648919e+02	564.8919071	26IL

26IL

Settings used

Pressure timeserie

Pressure calibration

Light

Light vs Pressure

Stationay period information